A smoothed bootstrap method is presented for the purpose of bandwidth selection in nonparametric hazard rate estimation for iid data. In this context, two new bootstrap bandwidth selectors are established based on the exact expression of the bootstrap version of the mean integrated squared error of some approximations of the kernel hazard rate estimator. This is very useful since Monte Carlo approximation is no longer needed for the implementation of the two bootstrap selectors. A simulation study is carried out in order to show the empirical performance of the new bootstrap bandwidths and to compare them with other existing selectors. The methods are illustrated by applying them to a diabetes data set.

Wastewater-based epidemiology (WBE) has become an effective tool in the surveillance of infectious diseases such as COVID-19. In this work, we performed a brief study of monitoring the SARS-CoV-2 viral load in wastewater from six nursing homes located in the metropolitan area of A Coruña (Spain) between December 2020 and March 2021. The main objective was to detect SARS-CoV-2 outbreaks among residents and study the efficacy of the vaccination campaign. SARS-CoV-2 viral load (RNA copies per L of wastewater) was determined by reverse-transcription quantitative PCR (RT-qPCR) using the quantification cycle (Cq) values for the nucleocapsid (N) gene. Our results showed that the increase in viral load preceded the increase in clinical cases, favoring an early warning system that detects COVID-19 outbreaks in advance, making it possible to contain and stop the transmission of the virus among residents. In addition, the efficacy of the new COVID-19 vaccines was evidenced, since after the vaccination campaign in nursing homes in A Coruña, it was observed that many residents did not present any symptoms of the disease, although they excreted high amounts of virus in their feces. WBE is a cost-effective strategy that should be implemented in all cities to prevent new emerging diseases or future pandemic threats.